Vicarious learning is happening when the patient learns a new behavior from an observation of a model performing the behavior to be learnt in a given situation and especially after having paid attention to the consequences of the model's behavior.
After a vicarious learning, the behavior of the patient should be under control of the same antecedent and subsequent events than those controlling the behavior of the model.
Virtual environments are commonly used today. Available processing power enables a providing of very realistic virtual environments.
Surprisingly, very few virtual environment applications are available for a therapeutic use in mental health. Available applications do not enable a user to configure an application for a patent, i.e. to customize it for a specific pathology to monitor or to cure.
Furthermore, it is usually not possible to collect pertinent data from the user in response to a virtual environment provided, which is a serious limitation if the virtual environment is provided for therapeutic purposes.
In fact, it will be appreciated that usually, it is not possible to know what aspect of the virtual environment is used at every moment by the patient.
In view of the above, there is a need for an apparatus that will provide a virtual environment which will overcome the above-identified drawbacks.